One Thousand Hours of RescueTime Data – Part 1: Getting Started

I spend a lot of time on the computer: 8-9 hours/day at my day job and another few at night and on weekends preparing for a startup.

Ironically, despite an proclivity for analysis and plenty of data to analyze, I’ve never taken the time to see exactly where all those hours go. I don’t have any data for my day job, but I do have RescueTime installed at home on both my Macbook and my PC, which has been busily recording my computer usage since I first installed it in July 2008.

I’d like to consider myself a pretty productive programmer, but before I embark on a new project, I wanted to see if there was anything I could do to improve. I spent the last several days going over this data and the results were, well, stunning. My reactions can be broken down into two broad categories: “Holy shit I spend a lot of time on the computer” and “Holy shit I waste a lot of time.” And so over the next several posts, I’ll be walking though an analysis of my 2009 RescueTime data as well as explaining, with code, how you can do the same.

Getting Started

RescueTime, for the unenlightened, is a free program that quietly logs information about what software you use and how much time you spend using it. The RescueTime software uploads that data to, which then displays it for you in a variety of nifty visualizations.

Here, for example, is a breakdown of my January 2009 Activities, as seen on my Dashboard:


There’s a few other visualizations too: efficiency summary, activities by day, breakdown by category, and a productivity analysis.

My only complaint about RescueTime is that there are not enough visualizations. For example: I want to see how much time I spend on the computer per week over the last year–how do I do it? How about average computer use per day of the week? Broken down by hour on each of those days? By month, how much time do I spend on websites? These are actionable metrics, but unless you do your own analysis or are prepared to navigate through dozens of different time periods on the dashboard, it’s not easy to get. My 2c: Have a separate page  with links to dozens of user-requested visualizations. Not everyone will want it, but it’ll be there for those that do. Could be a pro feature too.

To do your own analysis, you’ll first need to sign up for a Pro account so that you can download the data, which costs $8/mo.

Next, download your usage data by using the RescueTime API. Once you have an API key, simply go to the following URL to download your usage history:

There’s plenty of ways to customize the output per their API Documentation, but I found the one above gets me everything I need: organized by time and activity, formatted as a comma separated value file, broken down by hour, and spanning all of 2009.

Here’s what the file looks like:


We’ll use this Excel file to do all of the future analysis. When you save it, save it as a “Excel Macro-Enabled Workbook (*.xlsm)”, which will let you write macros to analyze the data.

For a quick example, you can total Column B, Time Spent, and divide by 3,600 to calculate the number of hours you spent on the computer. For me, that works out to be a whopping 3,018,243 seconds, or 997.52 hours. (You can also get this by clicking ‘year’ next to ‘show current’ at the top of the RescueTime dashboard).

Next post: How to calculate the average hours you spend per day on the computer broken down by month.


6 thoughts on “One Thousand Hours of RescueTime Data – Part 1: Getting Started

  1. I work on a similar time tracking product called Qlockwork ( ). That has a free 30 day trial and you can get your own data and analyse it during that trial. The 30 days is enough to give you a good idea about any time management issues that you have (for me it was excessive email. It was a big help to turn off email notifications and try to only look at email a few times a day, rather than every time anything came in).

  2. Data API transforms RescueTime from productivity gimmick to highly granular self-diagnostic | Maximum Koanic – Rough Draft

  3. Data API transforms RescueTime from productivity gimmick to highly granular self-diagnostic | CYBOrganization – Rough Draft

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